TeamStation AI / Executive decisions

Plan AI teams around the work they must own

AI workforce planning turns a delivery plan into roles, seniority, skills development, and sourcing choices. Start with the work that people must own, including review and support, before deciding how many seats to add.

Review the decision guide

At a glance

Describe the work
Separate implementation, evaluation, integration and support.
Assign role coverage
Match decision complexity, skills and review responsibility.
Choose the sourcing plan
Compare internal development, reassignment and managed delivery.

How it works

Work first, roles second, seats third

Scroll sideways to see the whole diagram. The same steps are written out below.

Work first, roles second, seats third

Describe the work
Separate implementation, evaluation, integration and support.
Assign role coverage
Match decision complexity, skills and review responsibility.
Choose the sourcing plan
Compare internal development, reassignment and managed delivery.

Work to coverData access and preparation
Validation taskExplain data permissions and demonstrate a reproducible preparation step.
Coverage decisionName a data owner and engineering backup.
Work to coverAI implementation
Validation taskChange a bounded feature and explain its failure modes.
Coverage decisionMatch seniority to decision complexity.
Work to coverEvaluation and release
Validation taskReview failed cases independently and explain the release decision.
Coverage decisionProtect reviewer capacity rather than assuming it is free.
Work to coverProduction support
Validation taskWork through a failed dependency and recovery scenario.
Coverage decisionAssign operating hours and escalation coverage.

The problem

A team built around model coding alone can leave data, testing, security, and production support unowned. For the CTO, busy engineers don't offset messy handoffs and a growing review queue.

Choose roles and seniority with evidence

Role mix

Cover product decisions, data, implementation, evaluation, and operations.

Owner: Engineering manager

Seniority

Match ambiguity, production authority, mentoring, and review duties to demonstrated experience.

Owner: Technical lead

Sourcing

Compare internal development and managed capacity against continuity, overlap, and access needs.

Owner: Engineering and procurement owners

A role plan still needs a workload check, because support and review consume the same finite capacity. Check workload against team capacity.

Illustrative scenario / not a client result

A model engineer cannot cover every delivery role

A company plans an AI feature inside an existing customer application. Model integration is only one part of the work. Someone must maintain data access, update the application, review incorrect outputs and support the feature after launch. Counting only model-building work understates the team requirement.

Develop existing staff: Choose training and supported practice where the team has adjacent skills and time to learn.
Reassign experienced staff: Move people when the required capability exists, while accounting for the work they leave behind.
Add managed seats: Add defined engineering coverage when the work, seniority and delivery responsibilities are clear.

The decision: Keep an accountable domain reviewer and production owner in the plan. Compare sourcing choices using the same work scope, support coverage and acceptance criteria. Don't turn an AI tooling decision into an unsupported headcount-reduction target.

Put the plan into practice

Step 1List recurring work and the decisions that require accountable people.
Step 2Map current team strengths and identify tasks without an owner or backup.
Step 3Choose a role mix, training plan, review coverage, and sourcing model.
Step 4Price the actual seat plan, then validate onboarding, access, time overlap, and support coverage.

Use the role-based planner for monthly seat estimates rather than importing a salary comparison. Estimate the engineering seats in your plan.

Role coverage and validation path

NIST includes risk management training for personnel and partners. NIST AI RMF 1.0 (2023), GOVERN 2.2.

TeamStation planning worksheet informed by the cited reference, not a customer result, certification, or completed assessment.

Scroll to see all columns. Focus the table and use the arrow keys.

Role coverage and validation path: evidence to collect before deciding
Work to cover	Validation task	Coverage decision
Data access and preparation	Explain data permissions and demonstrate a reproducible preparation step.	Name a data owner and engineering backup.
AI implementation	Change a bounded feature and explain its failure modes.	Match seniority to decision complexity.
Evaluation and release	Review failed cases independently and explain the release decision.	Protect reviewer capacity rather than assuming it is free.
Production support	Work through a failed dependency and recovery scenario.	Assign operating hours and escalation coverage.

What this does not establish

This is a role validation method, not a claim about any candidate or customer result. AI adoption alone does not prove that fewer engineers are needed.

Questions before you commit

How many engineers should an AI team have?

There is no universal team size. Define the workload, role coverage, review needs, support obligations, and available capacity before choosing seat counts.

What is the difference between workforce and capacity planning?

Workforce planning selects roles, skills, seniority, and sourcing. Capacity planning checks whether that team has enough available time and budget for the committed work.

From planning to delivery

What to scope with TeamStation

TeamStation scopes managed nearshore engineering seats around the work and seniority required. Bring the backlog, review responsibilities, time-zone needs and operating coverage before selecting a team.

A role and seniority plan tied to actual delivery tasks.
An explicit split between implementation, independent review and support.
A monthly engineering-seat scenario using the existing capacity planner.

An estimate is not a signed offer or proof of availability. Confirm scope and commercial terms separately; no salary ranges or productivity savings are inferred here.

Discuss your delivery scope

Your next decision

Plan AI engineering roles, seniority, review coverage and sourcing from real delivery work, then estimate monthly seats with TeamStation.

Price the roles and seats in your plan